Database Administrator

Position Name Database Administrator (Relational & Vector Databases AI Data Platform) Job No : KONE-14944 Position type: Permanent Total Exp: 4–6 years No of Position: 1 Notice Period: 15 Days - Immediate Asset: Laptop Mandatory for interview Work Location: Pune (Magarpatta City) Shift: US Shifts (Night Shift only) Work Type: Work from office Interview Rounds: 3 Interview Mode: Teams interview Shift Night Shift Department: Operations / Compliance / Legal Support

Job Description :

About KnovaOne Info: Founded in 2012 and headquartered in West Palm Beach, Florida, KnovaOne – A TRAKAmerica company is part of a leading legal and financial services group of companies with a strong U.S. presence and a skilled global workforce. Backed by over 40 years of combined leadership experience, we help 50+ law firms and top US financial institutions reduce costs, streamline operations, and deliver measurable business outcomes. Info: With a global team of 600+ employees and growing, we bring deep domain expertise in mortgage servicing, debt collections, bankruptcy, real estate transactions, accounts receivable management, back office and staffing support, and comprehensive recovery services, all underpinned by strict compliance frameworks and operational rigor. Role Summary Must Have We are looking for an experienced Database Administrator (DBA) who can manage and optimize traditional relational databases (Microsoft SQL Server) alongside modern Vector Databases used for AI, ML, and GenerativeAI workloads. Must Have The ideal candidate will be responsible for database installation, configuration, monitoring, performance tuning, security, backup/recovery, and operational excellence across both structured (SQL) and unstructured/vector-based data systems such as ChromaDB, Pinecone, and pgvector (PostgreSQL extension). Key Responsibilities Relational Database (MS SQL Server) Must Have Install, configure, and maintain Microsoft SQL Server (2019 / 2022) Must Have Perform routine DBA operations: Must Have Health checks Must Have Backup & recovery Must Have Patch management Must Have Index maintenance Must Have Monitor and optimize: Must Have Query performance Must Have Wait statistics Must Have Locking & blocking Must Have Resource utilization (CPU, memory, I/O) Must Have Implement High Availability & DR: Must Have Always On Availability Groups Must Have Replication Must Have Failover clustering Must Have Manage security: Must Have User access Must Have Encryption Must Have Auditing & compliance Must Have Proactively troubleshoot database issues and reduce downtime Vector Databases & AI Data Platforms Must Have Administer and support Vector Databases, like : Must Have Pinecone Must Have ChromaDB Must Have pgvector (PostgreSQL) Must Have Manage vector indexing, storage, and performance tuning Must Have Support AI/ML workloads such as: Must Have Semantic search Must Have Embeddings storage Must Have RAG (RetrievalAugmented Generation) patterns Must Have Assist development teams with: Must Have Vector schema design Must Have Embedding strategies Must Have Query optimization for similarity search Must Have Monitor latency, throughput, and scaling behavior of vector searches Must Have Ensure data durability, backups, and availability of vector data PostgreSQL (for pgvector) Must Have Install, configure, and manage PostgreSQL Must Have Enable and optimize pgvector extension Must Have Perform vacuum, reindexing, and performance tuning Must Have Manage rolebased security and replication Must Have Ensure compatibility between relational and vector workloads Monitoring, Automation & Operations Must Have Implement monitoring using tools such as: Must Have SQL Server Monitoring tools Must Have Prometheus / Grafana (where applicable) Must Have Cloud-native monitoring (Azure / AWS) Must Have Automate routine DBA tasks using: Must Have PowerShell Must Have SQL scripts Must Have Python (optional, but good to have) Must Have Define and maintain DB operational runbooks Must Have Participate in incident response, RCA, and performance reviews Cloud & Infrastructure (Good to Have) Must Have Experience with Azure SQL / Managed Instances or AWS RDS Must Have Understanding of: Must Have Containerized environments Must Have Kubernetesbacked databases (for AI workloads) Must Have Cost optimization strategies for cloud DB services Must Have Experience: Must Have 4–6 years overall database experience
1+ years with Vector DB / AI data platforms (hands on). Required Skills Core Database Skills Must Have Strong handson experience with MS SQL Server DBA Must Have Excellent SQL knowledge Must Have Performance tuning & query optimization Vector & AI Data Skills Must Have ChromaDB or Pinecone (or similar vector DB) Must Have pgvector on PostgreSQL Must Have Understanding embeddings & vector similarity search Must Have AI/ML data pipeline awareness (at a DBA support level) Tools & Scripting Must Have PowerShell / SQL scripting Must Have Basic Python (preferred) Must Have Backup, restore, automation scripts Preferred / NicetoHave Skills Good to have Knowledge of Azure OpenAI / LLM pipelines Good to have Experience supporting Generative AI platforms Good to have Exposure to data privacy & AI governance Good to have CI/CD integration for DB deployments Good to have Familiarity with DevOps / MLOps concepts Soft Skills Must Have Strong problemsolving skills Must Have Ability to work with AI engineers, backend developers, and architects Must Have Good documentation and communication skills Must Have Productionfirst mindset and ownership attitude Interview stages: Info: 2. Interview round of interview – Online Teams